1. Field
Embodiments of the disclosure relate to a humanoid robot that compensates for a zero moment point (ZMP) error during finite state machine (FSM)-based walking to achieve stable walking and a walking control method thereof.
2. Description of the Related Art
Research into a bipedal walking robot having a joint system similar to that of a human such that the robot may easily be applied to human working and living spaces has been actively conducted.
Examples of a walking control method of such a bipedalal robot include a position-based zero moment point (ZMP) walking control method, a torque-based dynamic walking control method, and a finite state machine (FSM) walking control method.
In the ZMP-based walking control method, a walking direction, a stride width, a walking rate and the like are preset, a walking pattern of feet and a body corresponding to the preset items is created using ZMP constraint conditions, and a joint position trajectory of each leg is calculated by inverse kinematic calculation of the walking pattern. Also, the ZMP-based walking control method is implemented by position servo control to enable joints of each leg to follow the calculated joint position trajectory. During walking, joints of each leg are controlled to accurately follow the joint position trajectory obtained from the walking pattern.
In the ZMP-based walking control method, the robot continues to bend its knees while walking such that kinematic singularity is avoided when calculating the angle of each joint through inverse kinematics. As a result, the robot may unnaturally walk unlike a human.
In the ZMP-based walking control method, the position of each joint may be accurately controlled to control the ZMP, and therefore, a position servo control gain is high. As a result, current of the motor is high, and therefore, energy efficiency is low. Also, rigidity of each joint is increased, and therefore, each joint may apply great impact to obstacles when colliding with the obstacles.
In the FSM-based walking control method, operation states (indicating the states of the FSM) of the walking robot are preset, and torque of each joint is calculated by referring to the operation states during walking, such that the robot walks appropriately.
In the FSM-based walking control method, the robot may take various poses by changing the operation state during walking. However, since each pose is taken in a restricted operation state, a separate operation to maintain balance of the robot is performed regardless of a walking operation to perform a task. A representative example of the balancing operation is a step motion in which the robot stamps its feet. Time is delayed and energy is wasted due to such operation.
The humanoid robot may be considered to interact with surroundings to apply FSM-based walking to the humanoid robot, such as a bipedal robot, which has difficulty in balancing as compared with a quadrupedal robot. That is, the operation state of the robot is fed back according to the surroundings to control the walking operation of the robot.